Senior ML Infra Engineer — Kubernetes & GitOps

Schrodinger, Inc.; New York (NY); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Healthcare

401k

Pre-tax commuter benefits

Flexible work schedule

Parental leave

Job summary

Schrödinger, Inc. is seeking a Senior Machine Learning Infrastructure Engineer in New York to build and maintain systems for ML models and AI agents in drug discovery.

You will own the infrastructure across our clusters and customer clouds on GCP and AWS, focusing on repeatable deployments, isolation, and cost-efficient GPU operations. Join a team delivering secure, scalable ML deployments with strong observability, SLOs, and on-call reliability in a fast-paced research environment.

Qualifications

• Six+ years of infrastructure, platform, or SRE experience.
• In-depth understanding of Kubernetes operation (beyond deployment).
• Robust background with GCP and familiarity with AWS.

Responsibilities

• Turn customer installs and upgrades into versioned, GitOps-driven releases (Helm, OpenTofu, Argo CD).
• Design isolation for multi-tenant agent sandboxes: network policy, identity, sandboxing, egress control.
• Secure CI/CD and software supply chain with keyless auth, ephemeral runners, signed images.
• Build and operate locked-down partner environments with private networking and audit logging.
• Keep GPU-heavy training and inference reliable with observability and SLOs.

Skills

Terraform

OpenTofu

Helm

GitOps

Python

Shell scripting

Least privilege

Communication

Tools

Kubernetes

GCP

AWS

Job description

Schrödinger, Inc. is seeking a Senior Machine Learning Infrastructure Engineer in New York to build and maintain systems for ML models and AI agents in drug discovery.

You will own the infrastructure across our clusters and customer clouds on GCP and AWS, focusing on repeatable deployments, isolation, and cost-efficient GPU operations. Join a team delivering secure, scalable ML deployments with strong observability, SLOs, and on-call reliability in a fast-paced research environment.